TanDEM-X elevation model data for canopy height and aboveground biomass retrieval in a tropical peat swamp forest
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Christiane Schmullius | Dirk H. Hoekman | Hans-Dieter Viktor Boehm | Steffen Kuntz | Michael Schlund | H. Boehm | C. Schmullius | D. Hoekman | M. Schlund | S. Kuntz | F. von Poncet | Felicitas von Poncet
[1] Ø. Dick,et al. SRTM DEM accuracy assessment over vegetated areas in Norway , 2007 .
[2] Cristopher Brack,et al. Tree biomass equations for tropical peat swamp forest ecosystems in Indonesia , 2014 .
[3] Maurizio Santoro,et al. Model-Based Biomass Estimation of a Hemi-Boreal Forest from Multitemporal TanDEM-X Acquisitions , 2013, Remote. Sens..
[4] Barbara Koch,et al. Status and future of laser scanning, synthetic aperture radar and hyperspectral remote sensing data for forest biomass assessment , 2010 .
[5] Terje Gobakken,et al. Estimating spruce and pine biomass with interferometric X-band SAR , 2010 .
[6] W. Cohen,et al. Lidar Remote Sensing for Ecosystem Studies , 2002 .
[7] S. E. Page,et al. Improving estimates of tropical peatland area, carbon storage, and greenhouse gas fluxes , 2015, Wetlands Ecology and Management.
[8] John D. Vona,et al. Vegetation height estimation from Shuttle Radar Topography Mission and National Elevation Datasets , 2004 .
[9] J. Bezerra. The Brazilian Amazon , 2015, World Forests.
[10] H. Balzter,et al. Forest canopy height and carbon estimation at Monks Wood National Nature Reserve, UK, using dual-wavelength SAR interferometry , 2007 .
[11] E. Næsset,et al. Forest biomass change estimated from height change in interferometric SAR height models , 2014, Carbon Balance and Management.
[12] David Miller,et al. The TerraSAR-X Satellite , 2010, IEEE Transactions on Geoscience and Remote Sensing.
[13] L. Iverson,et al. Biomass estimates for tropical forests , 1992 .
[14] Christiane Schmullius,et al. TanDEM-X data for aboveground biomass retrieval in a tropical peat swamp forest , 2015 .
[15] J. Swenson,et al. A comparison of lidar, radar, and field measurements of canopy height in pine and hardwood forests of southeastern North America , 2009 .
[16] Fábio Guimarães Gonçalves,et al. Vegetation profiles in tropical forests from multibaseline interferometric synthetic aperture radar, field, and lidar measurements , 2009 .
[17] C. Verwer,et al. Carbon pools in tropical peat forest : towards a reference value for forest biomass carbon in relatively undisturbed peat swamp forests in Southeast Asia , 2010 .
[18] L. Breiman,et al. Submodel selection and evaluation in regression. The X-random case , 1992 .
[19] M. Köhl,et al. Implications of sampling design and sample size for national carbon accounting systems , 2011, Carbon balance and management.
[20] Kamal Sarabandi,et al. Estimation of forest biophysical characteristics in Northern Michigan with SIR-C/X-SAR , 1995, IEEE Trans. Geosci. Remote. Sens..
[21] Christopher J. Banks,et al. Global and regional importance of the tropical peatland carbon pool , 2011 .
[22] Y. Hu,et al. Mapping the height and above‐ground biomass of a mixed forest using lidar and stereo Ikonos images , 2008 .
[23] Helen Amanda Fricker,et al. The ICESat-2 Laser Altimetry Mission , 2010, Proceedings of the IEEE.
[24] Annika Kangas,et al. Relative Efficiency of ALS and InSAR for Biomass Estimation in a Tanzanian Rainforest , 2015, Remote. Sens..
[25] Dan Johan Weydahl,et al. Detection of Forest Clear-Cuts with Shuttle Radar Topography Mission (SRTM) and Tandem-X InSAR Data , 2013, Remote. Sens..
[26] Peter Aldhous,et al. Land remediation: Borneo is burning , 2004, Nature.
[27] S. Solberg,et al. Temporal stability of InSAR height in a tropical rainforest , 2015 .
[28] J. Swenson,et al. Reference scenarios for deforestation and forest degradation in support of REDD: a review of data and methods , 2008 .
[29] Terje Gobakken,et al. Mapping and estimating forest area and aboveground biomass in miombo woodlands in Tanzania using data from airborne laser scanning, TanDEM-X, RapidEye, and global forest maps: A comparison of estimated precision , 2016 .
[30] G. Asner,et al. Environmental and Biotic Controls over Aboveground Biomass Throughout a Tropical Rain Forest , 2009, Ecosystems.
[31] I. Hajnsek,et al. Experiment Plan: INDREX II - Indonesian radar experiment campaign over tropical forest in L- and P-band , 2004 .
[32] Kim Worm Sorensen. Indonesian peat swamp forests and their role as a carbon sink , 1993 .
[33] S. Page,et al. Peat–water interrelationships in a tropical peatland ecosystem in Southeast Asia , 2008 .
[34] Data Acquisition, INDREX II - Indonesian Radar Experiment Campaign over Tropical Forest in L- and P-band, Version 1 , 2005 .
[35] João Roberto dos Santos,et al. Tropical-Forest Biomass Estimation at X-Band From the Spaceborne TanDEM-X Interferometer , 2015, IEEE Geoscience and Remote Sensing Letters.
[36] Erle C. Ellis,et al. High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision , 2013 .
[37] L. Dutra,et al. Tropical Forest Measurement by Interferometric Height Modeling and P-Band Radar Backscatter , 2005, Forest Science.
[38] Peter R. J. North,et al. Vegetation height estimates for a mixed temperate forest using satellite laser altimetry , 2008 .
[39] Anna Wendleder,et al. Validation of the absolute height accuracy of TanDEM-X DEM for moderate terrain , 2014, 2014 IEEE Geoscience and Remote Sensing Symposium.
[40] D. Burslem,et al. Estimating aboveground biomass in forest and oil palm plantation in Sabah, Malaysian Borneo using ALOS PALSAR data , 2011 .
[41] S. Page,et al. The amount of carbon released from peat and forest fires in Indonesia during 1997 , 2002, Nature.
[42] E. Suzuki,et al. Mortality and growth of trees in peat-swamp and heath forests in Central Kalimantan after severe drought , 2007, Plant Ecology.
[43] Hans-Dieter Viktor Boehm,et al. Multi-Temporal Airborne LiDAR-Survey and Field Measurements of Tropical Peat Swamp Forest to Monitor Changes , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[44] R. Treuhaft,et al. The calculated performance of forest structure and biomass estimates from interferometric radar , 2004 .
[45] Alan J. Lee,et al. Linear Regression Analysis: Seber/Linear , 2003 .
[46] S. Solberg,et al. Monitoring spruce volume and biomass with InSAR data from TanDEM-X , 2013 .
[47] M. Vastaranta,et al. Tandem-X interferometry in the prediction of forest inventory attributes in managed boreal forests , 2015 .
[48] W. Salas,et al. Benchmark map of forest carbon stocks in tropical regions across three continents , 2011, Proceedings of the National Academy of Sciences.
[49] R. B. Jackson,et al. CO 2 emissions from forest loss , 2009 .
[50] Marc Simard,et al. Canopy Height Model (CHM) Derived From a TanDEM-X InSAR DSM and an Airborne Lidar DTM in Boreal Forest , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[51] Florian Siegert,et al. Above ground biomass estimation across forest types at different degradation levels in Central Kalimantan using LiDAR data , 2012, Int. J. Appl. Earth Obs. Geoinformation.
[52] Göran Ståhl,et al. Model-assisted regional forest biomass estimation using LiDAR and InSAR as auxiliary data: A case study from a boreal forest area , 2011 .
[53] Iain H. Woodhouse,et al. Forest height estimation from X-band SAR , 2004, IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium.
[54] Michael B. Miller. Linear Regression Analysis , 2013 .
[55] S. Goetz,et al. Reply to Comment on ‘A first map of tropical Africa’s above-ground biomass derived from satellite imagery’ , 2008, Environmental Research Letters.
[56] E. Næsset,et al. Comparison of four types of 3D data for timber volume estimation , 2014 .
[57] Ron Kohavi,et al. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.
[58] V. D. Phillips. Peatswamp ecology and sustainable development in Borneo , 1998, Biodiversity & Conservation.
[59] Sandra A. Brown,et al. Monitoring and estimating tropical forest carbon stocks: making REDD a reality , 2007 .
[60] B. Nelson,et al. Improved allometric models to estimate the aboveground biomass of tropical trees , 2014, Global change biology.
[61] R. Dubayah,et al. Estimation of tropical forest structural characteristics using large-footprint lidar , 2002 .
[62] Leo Breiman,et al. Stacked regressions , 2004, Machine Learning.
[63] M. Hansen,et al. REDDcalculator.com: a web‐based decision‐support tool for implementing Indonesia’s forest moratorium , 2012 .
[64] J. Chambers,et al. Tree allometry and improved estimation of carbon stocks and balance in tropical forests , 2005, Oecologia.
[65] R. Xingu. ABOVEGROUND BIOMASS ESTIMATES FOR TROPICAL MOIST FORESTS OF THE BRAZILIAN AMAZON , 2004 .
[66] A. Baccini,et al. Mapping forest canopy height globally with spaceborne lidar , 2011 .
[67] João Roberto dos Santos,et al. Eucalyptus Biomass and Volume Estimation Using Interferometric and Polarimetric SAR Data , 2010, Remote. Sens..
[68] Malcolm Davidson,et al. INDREX II - indonesian airborne radar experiment campaign over tropical forest in L- and P-band: first results , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..
[69] Dan Johan Weydahl,et al. Temporal Stability of X-Band Single-Pass InSAR Heights in a Spruce Forest: Effects of Acquisition Properties and Season , 2015, IEEE Transactions on Geoscience and Remote Sensing.
[70] Wei-Yin Loh,et al. Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..
[71] L. Verchot,et al. Opportunities for reducing greenhouse gas emissions in tropical peatlands , 2010, Proceedings of the National Academy of Sciences.
[72] Sandra Englhart,et al. Quantifying Dynamics in Tropical Peat Swamp Forest Biomass with Multi-Temporal LiDAR Datasets , 2013, Remote. Sens..
[73] Juilson Jubanski,et al. ICESat/GLAS Data as a Measurement Tool for Peatland Topography and Peat Swamp Forest Biomass in Kalimantan, Indonesia , 2011, Remote. Sens..
[74] E. Næsset,et al. Monitoring forest carbon in a Tanzanian woodland using interferometric SAR: a novel methodology for REDD+ , 2015, Carbon Balance and Management.
[75] Josep G. Canadell,et al. Current and future CO 2 emissions from drained peatlands in Southeast Asia , 2009 .
[76] Sandra Englhart,et al. Aboveground biomass retrieval in tropical forests — The potential of combined X- and L-band SAR data use , 2011 .
[77] Heiko Balzter,et al. Validation of the TanDEM-X Intermediate Digital Elevation Model With Airborne LiDAR and Differential GNSS in Kruger National Park , 2016, IEEE Geoscience and Remote Sensing Letters.
[78] I. Hajnsek,et al. Final Report, INDREX II - Indonesian Radar Experiment Campaign over Tropical Forest in L- and P-band, Version 1 , 2006 .
[79] Ariel E. Lugo,et al. Biomass Estimation Methods for Tropical Forests with Applications to Forest Inventory Data , 1989, Forest Science.
[80] B. Koch,et al. Detection of individual tree crowns in airborne lidar data , 2006 .
[81] Soo Chin Liew,et al. Remotely sensed evidence of tropical peatland conversion to oil palm , 2011, Proceedings of the National Academy of Sciences.
[82] Birgit Wessel,et al. TanDEM-X Ground Segment – DEM Products Specification Document , 2013 .
[83] M. Rombach,et al. Description and applications of the multipolarized dual band OrbiSAR-1 InSAR sensor , 2003, 2003 Proceedings of the International Conference on Radar (IEEE Cat. No.03EX695).
[84] Gerhard Krieger,et al. TanDEM-X: A Satellite Formation for High-Resolution SAR Interferometry , 2006, IEEE Transactions on Geoscience and Remote Sensing.
[85] A. Lugo,et al. Wood Densities of Tropical Tree Species , 1992 .
[86] W. Walker,et al. Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR/InSAR, ETM+, Quickbird) synergy , 2006 .
[87] W Shotyk,et al. Interdependence of peat and vegetation in a tropical peat swamp forest. , 1999, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[88] Hidenori Takahashi,et al. Carbon fluxes from a tropical peat swamp forest floor , 2005 .
[89] Annette M. Molinaro,et al. Prediction error estimation: a comparison of resampling methods , 2005, Bioinform..